JOURNAL ARTICLE

Price Discrimination and Inventory Allocation in Bertrand Competition.

  • Published In: Manufacturing & Service Operations Management (M&SOM) (INFORMS), 2023, v. 25, n. 1. P. 148 1 of 3

  • Database: Business Source Ultimate 2 of 3

  • Authored By: COHEN, MAXIME C.; Jacquillat, Alexandre; Song, Haotian 3 of 3

Abstract

This article analyzes the interplay between price discrimination and inventory allocation in Bertrand competition involving two firms with differentiated product quality and heterogeneous customer segments—price-sensitive customers (PSCs) and quality-sensitive customers (QSCs). It establishes that customer heterogeneity acts as a market friction that allows firms to avoid the classic Bertrand price race to the bottom, benefiting the higher-quality firm with more quality-sensitive customers and the lower-quality firm with a more heterogeneous customer base. The study finds that price discrimination alone can intensify competition and reduce profits by eliminating this friction, but when combined with strategic (endogenous) inventory allocation that creates capacity constraints within segments, firms can restore market frictions and increase profits. Real-world examples motivating the model include regional pricing in fast fashion and vaccines, where firms commit inventory by segment. The results show that under low demand, price discrimination with strategic inventory allocation outperforms uniform pricing, whereas under high demand, uniform pricing can sometimes yield higher profits depending on market composition, highlighting the critical role of inventory management in designing competitive pricing strategies.

Additional Information

  • Source:Manufacturing & Service Operations Management (M&SOM) (INFORMS). 2023/01, Vol. 25, Issue 1, p148
  • Document Type:Article
  • Subject Area:Law
  • Publication Date:2023
  • ISSN:1523-4614
  • DOI:10.1287/msom.2022.1146
  • Accession Number:161468565
  • Copyright Statement:Copyright of Manufacturing & Service Operations Management (M&SOM) (INFORMS) is the property of INFORMS: Institute for Operations Research & the Management Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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